Numeric data is mostly made up of numbers but might use additional symbols to identify units.

Observational data is collected passively. Think website hits, class attendance, and sales numbers.

When referring to the size of the sample (the sample size), we'll use the notation N.

With independent events, your chances for an event do not increase or decrease based on past performance.

A data point is the intersection of an observation and a feature.

Working with professional data scientists or automated AI programs only requires the ability and the curiosity to ask good questions, to make connections between business issues and quantitative results, and to look out for dubious assumptions.

This process of iteration, discovery, and data scrutiny is known as exploratory data analysis (EDA). It was formulated by statistician John Tukey in the 1970s as a way to make sense of data with summary statistics and visualizations before applying more complex methods.

Probability drills-down: it uses a large universe of information to tell us what we'll find if we grab random scoops from it. Statistics drills-up: it tells us about the larger universe of information by using the small bits we have access to.

DIMENSIONALITY REDUCTION Dimensionality reduction is a process you're already familiar with. Photography is an example; it reduces the three-dimensional world down to a flat, two-dimensional photo you can carry in your pocket. With datasets, we're working with rows and columns: observations and features. The number of columns (features) in a datase